最后，针对模型的具体特点，设计模型解的编码方式，并采用基于云模型的参数自适应蚁群遗传算法进行仿真，结果表明了模型和算法的有效性。
At last, an effective algorithm model taking advance of a skillful encoding method is designed and called ACGA with self-adaptation adjustment of parameters based on cloud models.
该算法通过在蚁群算法中引入遗传算法的2 -交换变异算子，增强了算法的局部搜索能力，提高了解的质量。
It adopts 2-interchange mutation operator in ant colony algorithm to increase its ability of local search and to improve the quality of the solution.
为了解决多重模态最优化问题，我们运用了一维离散优化方法、遗传算法和蚁群算法。
To solve the multimodal optimization problem the 1d discrete optimization methods, the genetic and Ant Colony algorithms are applied.
为了解决多重模态最优化问题，我们运用了一维离散优化方法、遗传算法和蚁群算法。
To solve the multimodal optimization problem the 1d discrete optimization methods, the genetic and Ant Colony algorithms are applied.
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